def image_proposal(img_path):
img = skimage.io.imread(img_path)
img_lbl, regions = selective_search.selective_search(img,
scale=500,
sigma=0.9,
min_size=10)
candidates = set()
images = []
vertices = []
for r in regions:
# excluding same rectangle (with different segments)
if r['rect'] in candidates:
continue
if r['size'] < 220:
continue
#resize to 224 * 224 for input
proposal_img, proposal_vertice = prep.clip_pic(img, r['rect'])
# Delete Empty array
if len(proposal_img) == 0:
continue
#Ignore things contain 0 or not C contiguous array
x, y, w, h = r['rect']
if ((x == 0 or y == 0) and (w > 200 or h > 200)) or w == 0 or h == 0:
continue
# Check if any 0-dimension exist
[a, b, c] = np.shape(proposal_img)
if a == 0 or b == 0 or c == 0:
continue
im = Image.fromarray(proposal_img)
resized_proposal_img = resize_image(im, 224, 224)
candidates.add(r['rect'])
img_float = pil_to_nparray(resized_proposal_img)
images.append(img_float)
vertices.append(r['rect'])
return images, vertices
def image_proposal(img_path):
img = skimage.io.imread(img_path)
img_lbl, regions = selectivesearch.selective_search(
img, scale=500, sigma=0.9, min_size=10)
candidates = set()
images = []
vertices = []
for r in regions:
# excluding same rectangle (with different segments)
if r['rect'] in candidates:
continue
if r['size'] < 220:
continue
# resize to 224 * 224 for input
proposal_img, proposal_vertice = prep.clip_pic(img, r['rect'])
# Delete Empty array
if len(proposal_img) == 0:
continue
# Ignore things contain 0 or not C contiguous array
x, y, w, h = r['rect']
if w == 0 or h == 0:
continue
# Check if any 0-dimension exist
[a, b, c] = np.shape(proposal_img)
if a == 0 or b == 0 or c == 0:
continue
im = Image.fromarray(proposal_img)
resized_proposal_img = resize_image(im, 224, 224)
candidates.add(r['rect'])
img_float = pil_to_nparray(resized_proposal_img)
images.append(img_float)
vertices.append(r['rect'])
return images, vertices
def image_proposal(img_path):
img = cv2.imread(img_path)
img_lbl, regions = selectivesearch.selective_search(img,
scale=500,
sigma=0.9,
min_size=10)
candidates = set()
images = []
vertices = []
for r in regions:
# excluding same rectangle (with different segments)
if r['rect'] in candidates:
continue
# excluding small regions
if r['size'] < 220:
continue
if (r['rect'][2] * r['rect'][3]) < 500:
continue
# resize to 227 * 227 for input
proposal_img, proposal_vertice = prep.clip_pic(img, r['rect'])
# Delete Empty array
if len(proposal_img) == 0:
continue
# Ignore things contain 0 or not C contiguous array
x, y, w, h = r['rect']
if w == 0 or h == 0:
continue
# Check if any 0-dimension exist
[a, b, c] = np.shape(proposal_img)
if a == 0 or b == 0 or c == 0:
continue
resized_proposal_img = prep.resize_image(proposal_img,
config.IMAGE_SIZE,
config.IMAGE_SIZE)
candidates.add(r['rect'])
img_float = np.asarray(resized_proposal_img, dtype="float32")
images.append(img_float)
vertices.append(r['rect'])
return images, vertices
def image_proposal(img_path):
"""
using selective search to generate proposals of image
:param img_path:
:return:
"""
img = skimage_io.imread(img_path)
img_lbl, regions = selectivesearch.selective_search(img,
scale=500,
sigma=0.9,
min_size=10)
candidates = set()
images = []
vertices = []
for r in regions:
# excluding same rectangle
if r['rect'] in candidates:
continue
if r['size'] < 220:
continue
# resize to 224 * 224 for input
proposal_img, proposal_vertice = prep.clip_pic(img, r['rect'])
# delete empty
if len(proposal_img) == 0:
continue
x, y, w, h = r['rect']
if w == 0 or h == 0:
continue
[a, b, c] = np.shape(proposal_img)
if a == 0 or b == 0 or c == 0:
continue
im = Image.fromarray(proposal_img)
resized_proposal_img = prep.resize_image(im, 224, 224)
candidates.add(r['rect'])
img_float = prep.pil_to_nparray(resized_proposal_img)
images.append(img_float)
vertices.append(r['rect'])
return images, vertices